Paper Title
Feature Extraction And Classification Of FMRI Images
Abstract
Functional magnetic resonance imaging (fMRI) is widely used to identify neural correlates of cognitive tasks.
Statistical features like Correlation and Entropy are extracted from fMRI images of human brain of emotional and normal state
of mind. The features are based on texture properties of fMRI images. The features so extracted are classified using GMM and
kNN classifiers to help distinguish between normal and emotional state of human brain.